Nine biomarkers (APOC1, CHL1, FN1, VWF, PPBP, CLU, PRDX6, PRG4, and MMP9) in human serum were quantitatively analyzed using mass spectrometry, and the data were subsequently input into a novel deep-learning algorithm to detect breast cancer. Here, FN1 is linked to breast cancer.